Description:A METHOD FOR TRACKING WORTHINESS OF A FARM PRODUCE
FIELD OF INVENTION
The invention relates generally to the field of farm produce storage and supply chain, and more particularly to a method for tracking worthiness of a farm produce in a supply chain.
BACKGROUND
Farm produce includes commodities for human consumption including but not limited to fruits, vegetables, grains and livestock. Typically, a farm produce passes from a farm to processor for sorting and packaging, then to distributors for supplying it to retailers and finally to consumers. The farm produce may travel miles or spend days in storage before it reaches consumers. During the transit or during storage, the quality of the produce undergoes changes. The assessment of quality of a farm produce is important at every stage to enable a distributor/retailer to decide on the price to pay for the produce and for the consumer to make informed decision for nutritional quality and fitness for consumption. Accurate assessment of the quality to arrive at worthiness of a farm produce is crucial for ensuring food safety, optimizing supply chain management, and meeting consumer expectations. Providing worthiness of a farm produce is imperative for consumer health as it guides consumer to the safe and nutritious food having low levels of harmful bacteria or contaminants. It also provides quality assurance to the distributors and retailers as maintaining a high degree of worthiness enhances brand reputation and consumer trust. Further, efficient utilization of worthiness indices help in minimizing food waste and economic losses associated with spoiled or expired products. Tracking a farm produce from a farm till it reaches the consumers to monitor the changes in worthiness index is of immense significance/importance.
There are systems available in the art which track the farm produce in a supply chain. Eom et’al 2014, discloses a monitoring system for meat freshness detection, based on the smart RFID tag. Through combining the RFID technology with a gas sensor, temperature sensor, and humidity sensor, a relationship between meat freshness and gases released was obtained. The RFID tag measured the temperature, humidity, and ammonia during the distribution and storage processes, and the food poisoning index as a standard of judgment was used. CN103543703A discloses a food fresh keeping degree real-time monitor, the system includes a main control module, data acquisition module, wired sensor, wireless sensor, network communication module and power module, the power module is connected with main control module, data acquisition module, network communication module and wired sensor. The main control module is connected with network communication module, and the network communication module is connected and realizes remote data transmission function with remote monitoring center by wireless mode.
US20180285810A1 discloses systems and methods of block chain transaction recordation in a food supply chain. The method for tracking and recording data in a food supply chain system includes a computer system, a plurality of sensors, one or more block chain ledgers implemented on the computer system that interface with the plurality of sensors, tracking data relating to the food supply chain using the plurality of sensors and storing the tracked data using the one or more block chain ledgers.
Waldhans et’al 2023 discloses an app based system to monitor shelf life along the supply chain. The app-based system provides digital read-out of Time-Temperature Indicators (TTI) and a QR code scanner in the app for shelf life prediction.
One significant disadvantage of the systems herein above is that the systems do not provide tracking of dynamic changes in the quality of the food/ farm produce. Although there are methods for measuring freshness, there is a need to monitor the freshness in a supply chain. Hence, there is a need for a method that provides real time tracking of the farm produce to arrive at a worthiness index of the produce throughout the supply chain.
BRIEF DESCRIPTION OF DRAWINGS
So that the manner in which the recited features of the invention can be understood in detail, some of the embodiments are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.
FIG. 1 shows a schematic diagram of a high level architecture of a system for tracking of worthiness index of a farm produce, according to an embodiment of the invention.
FIG. 2 shows a representative screenshot of the user interface of the system for tracking of worthiness index of a farm produce, according to an embodiment of the invention.
SUMMARY OF THE INVENTION
One aspect of the invention provides a method for tracking worthiness of a farm produce in a supply chain. The method includes analyzing the farm produce for a plurality of parameters. The parameters that are analyzed include physical parameters, chemical parameters, microbiological parameters and sensory parameters. Subsequently, a change in the parameters is estimated by tracking the produce through the supply chain. A weighted average is then obtained for each of the plurality of parameters to arrive at a plurality of scores. The scores are based on factors including time for which the farm produce is in transit and/or storage, and conditions of transit and/or storage. A worthiness index of the farm produce is determined based on the plurality of scores. The worthiness index as determined provides worthiness of a farm produce in a supply chain and/or is in storage.
DETAILED DESCRIPTION OF INVENTION
Various embodiments of the invention provide a method for tracking worthiness of a farm produce in a supply chain.
The terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting of the invention. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, the use of the terms a, an, etc. does not denote a limitation of quantity, but rather denotes the presence of at least one of the referenced items. It will be further understood that the terms “comprises” and/or “comprising,” or “includes” and/or “including” when used in this specification, specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, regions, integers, steps, operations, elements, components, and/or groups thereof. It will be further understood that for the purposes of this disclosure, “at least one of” will be interpreted to mean any combination of the enumerated elements following the respective language, including combination of multiples of the enumerated elements.
Unless otherwise defined, all terms used herein have the same meaning as commonly understood by one of ordinary skills in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Throughout the drawings and the detailed description, unless otherwise described, the same drawing reference numerals are understood to refer to the same elements, features, and structures. The relative size and depiction of these elements may be exaggerated for clarity, illustration, and convenience.
The term user, consumer and customer are used interchangeably throughout the description.
The term farm produce and produce are used interchangeably throughout the description.
Various embodiments of the invention provide a method for tracking worthiness of a farm produce in a supply chain. The method provides for determining a worthiness index of a farm produce and tracking of worthiness of the farm produce in a supply chain and/or in the storage. Worthiness includes but is not limited to the quality of a farm produce, freshness, and fitness for consumption. Further, the worthiness is for storage, consumption of a farm produce and for seed storage for multiple reproductions. The farm produce includes perishable as well as non perishable food products and includes but is not limited to fruits, vegetables, grains, dairy products, meat and livestock. The first step of the method includes analyzing the farm produce for a plurality of parameters. The farm produce obtained after harvesting is analyzed for a plurality of parameters. The parameters include but are not limited to physical parameters, chemical parameters, microbiological parameters and sensory parameters. The physical parameters include visual appearance of the farm produce like colour, texture; olfactory parameters like aroma, odour, pungency, putridity; firmness, presence of external material, presence of insects, fungal infestation and moisture. In one embodiment of the invention, the physical parameters analyzed for grains include discolored grains, broken grains, insect infested grains, fungus infested grains, external material, admixture and moisture. The chemical parameters include but are not limited to pH, acidity and volatile compounds. The microbiological parameters include but are not limited to bacterial count, presence of mold and yeast. The analysis of sensory parameters includes analyzing the farm produce for taste, smell and texture. The farm produce is analyzed for the physical parameters, chemical parameters, microbiological parameters and sensory parameters using standard procedures. The data comprising the values obtained for each of the plurality of parameters is collected and recorded. In one embodiment of the invention, the data of the physical parameters, chemical parameters, microbiological parameters and sensory parameters is uploaded in a central server. The farm produce is then tracked through the supply chain for estimating any changes in the plurality of parameters. The farm produce is tracked from the time it leaves a processing unit and is in transit or is in storage till it reaches the consumers. The produce is tracked through means that include but is not limited to RFID tags, QR codes or a combination thereof. The farm produce is tagged with a RFID tag and/or a QR code for tracking through the supply chain. The tracking means consists of unique identification information and additional data such as production date, expiration date, batch number and storage and/or transit conditions like temperature, humidity, gas concentration. The factors influencing the transit and/or storage conditions including but not limited to temperature, humidity and gas concentrations are monitored through a plurality of sensors. The plurality of sensors includes but is not limited to temperature sensor, humidity sensor, pH sensor and gas sensor. The plurality of sensors are integrated into the supply chain including but not limited to storage units, transport vehicles and processing units. The plurality of sensors periodically send data on temperature, humidity and gas concentration to the central server through IoT devices, such as gateways, that facilitate data transmission via wireless networks like Wi-Fi, Bluetooth, or cellular networks.
RFID tag readers and QR code scanners read the RFID tags and QR codes, respectively throughout the supply chain. The data from the RFID tag readers and QR code scanners is uploaded in the central server.
A change in each of the plurality of parameters as affected by the storage and/or transit conditions is estimated. For estimating change in parameters, the real-time data collected from the plurality of sensors is compared against the values that are obtained after the farm produce is harvested. Advanced analytics and algorithms including statistical methods, mathematical models and machine learning models analyze these changes over time. In an example, time-temperature integrators might use accumulated temperature data to predict spoilage. In another example, the method uses trend analysis and anomaly detection algorithms to identify significant deviations from expected patterns. The mathematical models include but are not limited to time-temperature integrators, Arrhenius equations and kinetic models. The machine learning models include but are not limited to regression models, decision trees, and neural networks.
Subsequently, a weighted average for each of the plurality of parameters is obtained. Each parameter is assigned a weight (wi) based on its relative significance in determining worthiness. For example, appearance and aroma may be accorded a higher weight as compared to microbial load. In one embodiment of the invention, the weights assigned to some physical parameters are:
Appearance: w1 = 0.4
Aroma: w2 = 0.3
Texture: w3= 0.2
Microbial load: w4 = 0.1
A normalized value of each parameter is then obtained by normalizing on a predefined scale. Parameters are normalized to ensure that they are comparable on a common scale. The parameters are normalized using normalization techniques that include but are not limited to minimum-maximum normalization, z-score normalization and scaling factors normalization. In one example, the values are normalized using minimum-maximum normalization by using the formula:
Normalized Value= (Actual Value-Min Value) / (Max Value-Min Value)
The weighted average for each parameter is then calculated using the formula:
Weighted Average= ?i= 1n(wi x pi)
where:
???? = Weight assigned to parameter
pi = Normalized value of parameter
n = Total number of parameters
The method further includes arriving at a plurality of scores based on time for which the farm produce is in transit and/or storage, conditions of transit and/or storage. The scores are generated based on time, for instance number of days, the produce is in transit and/ or is in storage. In one embodiment of the invention, the scores are generated based on the number of days the produce is in transit and the temperature at which the produce is stored while in the transit. From the plurality of scores, a worthiness index is determined. The worthiness index is calculated as weighted average of the plurality of scores. The worthiness index of the farm produce as tracked through the supply chain provides accurate monitoring of the farm produce throughout the supply chain facilitating effective management of the farm produce. The worthiness index of the farm produce enables a user to make informed decision on fitness of consumption of the farm produce.
Various embodiments of the invention provide a system for tracking worthiness of a farm produce. FIG. 1 shows a schematic diagram of a high level architecture of a system for tracking of worthiness index of a farm produce, according to an embodiment of the invention. The system includes a data collection module 101, a data processing module 103, a tracking module 105 for real time monitoring and a user interface 107. The data collection module 101 includes sensors for measuring physical, chemical, and microbiological parameters. The data collection module further includes data input devices including but not limited to computers, smartphones and tablets for capturing sensory evaluation data using Wi-Fi/ Bluetooth. The data processing module 103 includes a centralized server for storing and processing data, for calculating weighted averages and worthiness index. The tracking module 105 includes RFID tags and/or QR codes attached to the produce for real-time tracking and RFID readers and /or QR code scanners for data collection throughout the supply chain and IOT sensors for monitoring environmental conditions like temperature, humidity and gas concentration. The user interface provides real time data visualization, tracking information and worthiness index of the farm produce. FIG. 2 shows a representative screenshot of the user interface of the system for tracking of worthiness index of a farm produce, according to an embodiment of the invention. The user interface includes a display for displaying worthiness index of a farm produce including graphs and charts for providing visual representation of data trends over time and across a plurality of parameters. The user interface includes an input device configured to allow input of data obtained from analysis of plurality of parameters and means for automated uploading of data from RFID and QR code systems. The user interface also provides real-time updates displaying current location and status of produce based on RFID and sensor data. Alerts and notifications for approaching expiration dates or deviations in storage conditions, generation of reports on worthiness indices, scores, and shelf life estimate and exporting of data in various formats is also provided.
The foregoing description of the invention has been set merely to illustrate the invention and is not intended to be limiting. Since modifications of the disclosed embodiments incorporating the spirit and substance of the invention may occur to person skilled in the art, the invention should be construed to include everything within the scope of the appended claims and equivalents thereof.

, Claims:We Claim:
1. A method for tracking worthiness of a farm produce in a supply chain, the method comprising:
analysing the farm produce for a plurality of parameters wherein the plurality of parameters include physical parameters, chemical parameters, microbiological parameters and sensory parameters;
estimating change in the parameters by tracking the produce through the supply chain;
Obtaining a weighted average for each of the plurality of parameters;
arriving at a plurality of scores wherein the scores are based on time and conditions of storage and/or transit; and
determining a worthiness index of the farm produce based on the plurality of scores.
2. The method as claimed in claim 1, wherein tracking the worthiness of the farm produce is performed in real-time throughout the supply chain.
3. The method as claimed in claim 1, wherein the farm produce includes perishable farm produce and non-perishable farm produce.
4. The method as claimed in claim 1, wherein the physical parameters include visual appearance of the farm produce like colour, texture; olfactory parameters like aroma, odour, pungency, putridity; firmness, presence of external material, presence of insects, fungal infestation and moisture.
5. The method as claimed in claim 1, wherein the chemical parameters include pH, acidity and volatile compounds.
6. The method as claimed in claim 1, wherein the microbial parameters include bacterial count, presence of mold and presence of yeast.
7. The method as claimed in claim 1, wherein the sensory parameters include taste, smell and texture.
8. The method as claimed in claim1, wherein the tracking of the farm produce is achieved through RFID or QR code or a combination thereof.
9. The method as claimed in claim 1, wherein the weighted average is obtained by formula ?i= 1n(wi x pi) where ???? is weight assigned to parameter, pi is normalized value of parameter and n is total number of parameters.
10. A system for tracking worthiness of a farm produce in a supply chain, the system comprising:
a data collection module (101) for collecting data on the plurality of parameters and on changes in plurality of parameters during storage and/or transit of the farm produce;
a data processing module (103) for storing and processing data wherein processing includes calculating weighted averages and worthiness index;
a tracking module (105) for real time monitoring of the farm produce throughout the supply chain; and
a user interface (107) for real time data visualization, tracking information and worthiness index of the farm produce.

Bangalore ANJU RAWAT September 13, 2024 (IN/PA/3151)
(INTELLOCOPIA CONSULTING LLP)
AGENT FOR APPLICANT